Shenling Qige Granules (SLQG), derived from the Qing Dynasty formula Qige San recorded in Yi Xue Xin Wu, has been used in clinical practice in China as an adjuvant traditional Chinese medicine preparation for esophageal squamous cell carcinoma (ESCC), but its molecular basis remains unclear. This study investigated the antitumor effects and mechanisms of SLQG using TE-1 xenograft mice and SLQG-containing serum-treated TE-1 cells. Transcriptome sequencing, network pharmacology, molecular docking, molecular dynamics simulation, and public-database analysis were integrated to prioritize candidate mechanisms. Histological, molecular, cellular, and siRNA-mediated decorin (DCN) knockdown assays were performed for validation. SLQG, especially at the medium dose, inhibited xenograft tumor growth and increased DCN expression. Transcriptomic analysis highlighted the transforming growth factor-β (TGF-β)/Smad pathway. In silico analyses suggested that several SLQG-derived compounds, particularly ursolic acid, may be associated with DCN-related regulation. Public-database analysis indicated lower DCN expression in esophageal carcinoma tumor samples than in normal samples and an association with pathological stage. In vivo and in vitro, SLQG increased DCN expression, reduced Smad2/3 phosphorylation, promoted pro-apoptotic signaling, and induced G0/G1 arrest; these effects were attenuated by DCN knockdown. These findings suggest that SLQG inhibited ESCC progression in TE-1 xenograft and cell-based models, potentially through modulation of the DCN-associated TGF-β/Smad signaling axis.

The classification of skin cancer remains a challenging task because of the subtle visual patterns of benign and malignant lesions. In this work we propose an interpretable ensemble learning framework for dermoscopic skin lesion classification by combining Random Forest, XGBoost and LightGBM using Max-Voting. The proposed system demonstrates good predictive performance with clinical interpretability, achieving 95.94% accuracy on the HAM10000 dataset. To increase transparency we use explainable AI techniques to visualise the image regions and features that are most important for the model's decisions. We also perform feature selection based on Genetic Algorithm to select the most discriminative descriptors and to reduce the redundancy in the hybrid feature space. The combination of deep features, handcrafted features, ensemble learning and explainability leads to a strong framework for accurate prediction and meaningful interpretation. The experimental results show that the proposed approach outperforms the individual classifiers and provides more explainable clinically relevant explanations that may help to improve the confidence and trust of dermatologists. In summary, the study demonstrates that the combination of ensemble learning and explainable AI can provide an effective and practical direction towards trustworthy skin cancer decision support.

Immune-active hepatocellular carcinoma (HCC) is commonly treated as a single inflamed phenotype, although its internal immune heterogeneity remains incompletely defined. We integrated public bulk transcriptomic, single-cell, spatial transcriptomic, proteomic, phosphoproteomic, and treatment-cohort data to test whether this heterogeneity is better represented by discrete states or a continuous immune axis. In 112 checkpoint-high TCGA-LIHC tumors, an inflamed-minus-myeloid axis showed structured heterogeneity but no robust empirical bimodality: the observed kernel-density curve had one prominent mode and none of 1,000 bootstrap resamples contained two or more prominent modes. IFNγ-responsive-associated and myeloid-suppressive-associated labels were therefore retained only as operational summaries of opposing axis tendencies, and the biological polarity persisted across alternative definitions of immune-active entry. A fixed 10-gene within-sample rank template-contrast score transferred the axis to independent HCC cohorts. Transcriptomic analyses based on gene sets non-overlapping with the compact panel and original state-defining genes supported the IFNγ-oriented end, whereas spatial analyses showed local cross-end coexistence with reduced immediate-neighbor mixing relative to a count-preserving random-label null, and paired proteomic/phosphoproteomic analyses showed concordant myeloid-oriented associations involving macrophage, fibroblast/extracellular-matrix, hypoxia, SPP1-integrin-FAK, and myeloid-receptor programs. Direct application of the frozen transfer score to four public HCC immunotherapy cohorts yielded heterogeneous, imprecise response associations (pooled Hedges' g = 0.10, 95% CI -0.42 to 0.61) and did not establish clinical response prediction. These results support a structured IFNγ-responsive-to-myeloid-suppressive continuum within immune-active HCC. The framework is transferable across public datasets but requires prospective HCC-specific clinical validation, while functional perturbation studies are needed before causal or therapeutic claims.

To investigate the roles of RPARP-AS1 and miR-10b-5p in regulating the prognosis and tumor progression of non-small cell lung cancer (NSCLC).

A total of 138 NSCLC patients were enrolled. Surgical specimens were stored in liquid nitrogen. All patients received 5 years of clinical follow-up for prognostic assessment. In addition, multivariate Cox regression analysis was conducted to identify independent factors affecting NSCLC prognosis, and gene expression levels were quantified by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Cell Counting Kit-8 (CCK-8) assays were performed to examine cell proliferation, and transwell assays were used to assess cell migration and invasion. Furthermore, nuclear-cytoplasmic fractionation experiments were conducted to localize RPARP-AS1 distribution. The interaction between RPARP-AS1 and miR-10b-5p was examined by dual luciferase reporter assays, and downstream targets in NSCLC were predicted using databases.

RPARP-AS1 was downregulated, while miR-10b-5p was upregulated in both NSCLC patient tissues and cells. Patients with reduced RPARP-AS1 expression or increased miR-10b-5p expression had lower survival rates, accompanied by worsened tumor size, differentiation, and metastasis. oe-RPARP-AS1 inhibited tumor cell proliferation, migration, and invasion. However, RPARP-AS1-induced functional alterations in NSCLC cells were mediated by miR-10b-5p. A total of 47 overlapping genes were identified to potentially mediate downstream signaling pathways of the RPARP-AS1/miR-10b-5p axis in NSCLC cells.

Silencing RPARP-AS1 targeted miR-10b-5p to induce NSCLC cell proliferation, migration, and invasion, leading to tumor progression and poor prognosis.

Hepatocellular carcinoma is the sixth most common cancer worldwide and a leading cause of cancer related mortality. Risk factors include chronic hepatitis B/C, obesity, alcohol abuse, diabetes and metabolic disorders. In advanced stages, normal treatments such as surgery, transplantation and chemotherapy are not as effective as tumors develop resistance and do not target oncogenic pathways well. Small interfering RNA (siRNA) therapeutics have the potential to change treatment paradigms by silencing specific biological pathways, thus suppressing tumor progression. Polymeric nanoparticles (PNPs) such as poly(lactic-co-glycolic acid) (PLGA), polyethyleneimine (PEI) and stimuli-responsive copolymers have attracted attention as effective delivery systems for siRNA. These carriers protect siRNA from enzymatic degradation and facilitate its cellular uptake. Furthermore, the surface of the carriers can be modified with targeting ligands, eg, galactose or ASGPR antibodies, to improve tumor-specific delivery. The PNPs can be tuned to change their physical and chemical properties, are more stable and responsive to signals from the tumor microenvironment for regulated release. This means they perform better than lipophilic or metallic carriers. Hepatocyte specific absorption pathways even enhance the liver tropism. This review focuses on recent advances in siRNA based therapeutic strategies against hepatocellular carcinoma, with a special focus on PNPs mediated drug delivery systems. It describes significant oncogenic pathways like β-catenin and STAT3 and formulation techniques including nanoprecipitation and layer by layer assembly. The review also reports the increasing importance of artificial intelligence in siRNA design, formulation optimization, and personalized therapeutic methods to improve the clinical applicability of HCC treatment.

Hepatoid carcinoma of the ovary (HCO) exhibits morphological and immunophenotypic features highly similar to those of hepatocellular carcinoma. Immunohistochemical staining for alpha-fetoprotein, hepatocyte paraffin antigen 1, and glypican-3 is an important auxiliary approach for the clinical diagnosis of HCO. Currently, most treatment regimens for this disease are developed with reference to clinical management protocols for high-grade epithelial ovarian cancer. Hepatoid carcinoma of the ovary (HCO) is an extremely rare, distinct histological subtype of primary ovarian adenocarcinoma that exhibits remarkable clinicopathological similarity to hepatocellular carcinoma (HCC). The histogenetic origin of HCO remains controversial, with hypotheses proposing derivation from ovarian surface epithelium or extragonadal non-germ cell precursors. This neoplasm primarily affects postmenopausal women, typically presenting as unilateral or bilateral cystic-solid ovarian masses accompanied by significantly elevated serum alpha-fetoprotein (AFP) levels. HCO is characterized by high biological aggressiveness, with most cases diagnosed at an advanced stage leading to a uniformly poor prognosis. Owing to its extreme rarity, existing research on HCO is largely limited to sporadic case reports. This systematic review aggregates eligible HCO cases published from 1987 to January 2026, conducts pooled analysis and comprehensive synthesis of clinical characteristics, pathological features, treatment strategies and molecular findings, with the aim of providing evidence-based references for clinical diagnosis and therapeutic decision-making, and establishing a theoretical foundation for future translational research.

Immunotherapy has markedly improved outcomes across multiple cancer types; however, colorectal cancer (CRC) remains largely refractory, with meaningful responses mostly restricted to tumors harboring deficient mismatch repair and high microsatellite instability (dMMR/MSI-H), which represent only a small fraction of CRC cases. Emerging evidence suggests that mitochondrial dysfunction may be viewed as a metabolic checkpoint, representing a conceptual framework through which mitochondrial-dependent processes regulate antitumor immunity and immunotherapy response in CRC. In tumor cells, mitochondrial reprogramming enhances reliance on oxidative phosphorylation, promotes hypoxia, and drives metabolite accumulation, collectively shaping an immunosuppressive tumor microenvironment. In parallel, tumor-infiltrating T-cells exhibit mitochondrial dysfunction characterized by impaired biogenesis, reduced respiratory capacity and features of exhaustion, thereby limiting the efficacy of immune checkpoint inhibitors (ICIs). In this review, we summarize current insights into the role of mitochondrial pathways in regulating tumor immune escape and T-cell dysfunction in CRC. We further discuss emerging therapeutic strategies aimed at targeting metabolic vulnerabilities to overcome resistance and potentially enhance responses to immunotherapy.

Hibernoma is an uncommon benign adipocytic neoplasm showing differentiation toward brown fat. Although it usually occurs in anatomical sites where residual brown adipose tissue persists, retroperitoneal involvement is particularly uncommon, with fewer than 60 cases reported.

A 54-year-old man was found to have a retroperitoneal mass incidentally during a routine physical examination. CT and MRI demonstrated a 15-cm homogeneous fat-containing lesion without radiological evidence of local invasion. Complete surgical excision was performed. Histopathological examination showed univacuolated and multivacuolated adipocytic cells without atypia. The tumor was positive for S-100 and CD10, and fluorescence in situ hybridization showed no MDM2 amplification, supporting the diagnosis of hibernoma. Recovery was uneventful, and the patient was discharged on Postoperative Day 7.

Retroperitoneal hibernoma can be difficult to distinguish radiologically from other lipomatous neoplasms, including atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL). Diagnosis therefore relies on the integration of morphology with ancillary immunohistochemical and, when indicated, molecular findings. The decision between preoperative core needle biopsy and upfront resection should be individualized according to the radiological differential diagnosis, tumor vascularity and resectability, expected surgical morbidity, and whether tissue confirmation would alter management.

Hibernoma should be included in the differential diagnosis of retroperitoneal fat-containing masses. Accurate diagnosis is fundamental, as complete surgical excision is curative, with no need for additional treatment.

Lymph node metastasis (LNM) is a critical factor contributing to poor prognosis in esophageal squamous cell carcinoma (ESCC) patients. Consequently, elucidating its molecular mechanisms and identifying effective therapeutic targets have become a paramount challenge in clinical practice.

Plasma samples were systematically collected from healthy individuals, ESCC patients without LNM, and those with LNM. Extracellular vesicles (EVs) were isolated from plasma by size-exclusion chromatography (SEC) and ultracentrifugation (UC) methods, and EV-derived miRNA expression profiles were detected and compared by sequencing. Differentially expressed miR-1246 was selected, and a diagnostic model based on plasma EV-miR-1246 was established to predict LNM. The biological functions of EV-miR-1246 and its target gene PPP2CB, which was identified by mass spectrometry combined with online target prediction methods, in the LNM of ESCC were further investigated using in vitro cellular assays and in vivo animal models. Rescue experiments and NF-κB agonist functional assays were performed to verify the downstream regulatory axis.

MiR-1246 levels were significantly elevated in plasma extracellular vesicles from ESCC patients with lymph node metastasis. The diagnostic model established based on vesicular miR-1246 showed favorable predictive efficacy for lymph node metastasis status in ESCC. In vitro functional experiments confirmed that vesicular miR-1246 derived from ESCC cells significantly enhanced the migration, invasion, and tube formation capacities of human lymphatic endothelial cells (HLECs). In vivo mouse experiments further confirmed that vesicular miR-1246 derived from ESCC cells significantly promoted lymph node metastasis of esophageal squamous cell carcinoma in mice. Mechanistically, miR-1246 targets and represses PPP2CB expression. Rescue experiments further confirmed that the miR-1246/PPP2CB axis activates NF-κB signaling, thereby promoting lymphatic endothelial activation and lymphangiogenesis.

This study demonstrates that EV-derived miR-1246 acts as a promising predictive biomarker for lymph-node metastasis in ESCC. Mechanistically, EV-delivered miR-1246 targets PPP2CB to activate NF-κB signaling, thereby driving lymphatic endothelial activation and lymph node metastasis. These findings offer novel diagnostic biomarkers and therapeutic targets for ESCC patients with lymph node metastasis.

Obesity, recognized as a significant global public health issue, has garnered widespread attention. The chronic systemic inflammatory state characteristic of obesity may act as a key pathophysiological factor in the development of obesity-related cancers. Based on a structured literature search of peer-reviewed databases, this review summarizes the features of the inflammatory microenvironment within adipose tissue in obesity, encompassing adipocyte hypertrophy and hyperplasia, hypoxia, and endoplasmic reticulum stress; activation of pro-inflammatory cytokines and signaling pathways; and the polarization of immune cells towards a pro-inflammatory phenotype. We emphasize the molecular mechanisms that link inflammation to carcinogenesis and explore targeted therapeutic strategies against inflammation, such as cytokine and receptor blockade, immune cell reprogramming, natural anti-inflammatory agents, and nanoparticle drug delivery systems. This review highlights the mechanistic link between obesity, inflammation, and cancer, providing insights for the development of precise preventive and therapeutic approaches for obesity-associated inflammation and tumorigenesis.